‘Rachel's not here’: Constructed dialogue in gossip

Sociolinguistic research has demonstrated that gossip is a co‐constructed phenomenon, which allows participants to establish solidarity and build alignments with each other, while evaluating an absent party. Gossip can also serve important social functions, such as helping to establish and reconfirm group norms and values. The present study provides a detailed analysis of an extended gossip episode that occurred within an institutional context: a study group interaction at a U.S. university. Our analysis shows how, in gossip, constructed dialogue both prompts and legitimizes pejorative evaluations towards an absent third party, and is actually the pivot around which group members negotiate values and norms in the process of arriving at a shared moral stance. Our analysis also demonstrates that alignment in gossip interactions is tenuous and must be continuously renewed.     

A general inverse sampling scheme and its application to adaptive cluster sampling

Not having a variance estimator is a seriously weak point of a sampling design from a practical perspective. This paper provides unbiased variance estimators for several sampling designs based on inverse sampling, both with and without an adaptive component. It proposes a new design, which is called the general inverse sampling design, that avoids sampling an infeasibly large number of units. The paper provide estimators for this design as well as its adaptive modification. A simple artificial example is used to demonstrate the computations. The adaptive and non‐adaptive designs are compared using simulations based on real data sets. The results indicate that, for appropriate populations, the adaptive version can have a substantial variance reduction compared with the non‐adaptive version. Also, adaptive general inverse sampling with a limitation on the initial sample size has a greater variance reduction than without the limitation.     

Bayesian and Robust Bayesian analysis under a general class of balanced loss functions

For estimating an unknown parameter θ, we introduce and motivate the use of balanced loss functions of the form L_{r, w, d0}(q, d)=wr(d₀, d)+ (1-w) r(q, d){L_{\rho, \omega, \delta_0}(\theta, \delta)=\omega \rho(\delta_0, \delta)+ (1-\omega) \rho(\theta, \delta)}, as well as the weighted version q(q) L_{r, w, d0}(q, d){q(\theta) L_{\rho, \omega, \delta_0}(\theta, \delta)}, where ρ(θ, δ) is an arbitrary loss function, δ ₀ is a chosen a priori “target” estimator of q, w ? [0,1){\theta, \omega \in[0,1)}, and q(·) is a positive weight function. we develop Bayesian estimators under L_{r, w, d0}{L_{\rho, \omega, \delta_0}} with ω > 0 by relating such estimators to Bayesian solutions under L_{r, w, d0}{L_{\rho, \omega, \delta_0}} with ω = 0. Illustrations are given for various choices of ρ, such as absolute value, entropy, linex, and squared error type losses. Finally, under various robust Bayesian analysis criteria including posterior regret gamma-minimaxity, conditional gamma-minimaxity, and most stable, we establish explicit connections between optimal actions derived under balanced and unbalanced losses.     

The Assessment of Quality of Life in Transitional Neighborhoods

Quality of life (QoL) is being considered as one of the fundamental concepts in contemporary era. It tries to assess the level of general welfare of the communities. Urban transitional neighborhoods possess specific situation and as a result present distinctive QoL. The major objective of this study is to identify and measure the QoL dimensions in urban transitional neighborhoods using both objective and subjective indices pertaining to Darvazeshemiran neighborhood of Tehran. In order to accomplish this and gather needed data, 244 questionnaires were distributed among Darvazeshemiran’s residents. This study suggests that there exists low level of QoL in the study area. That is 64.3 % of the residents were dissatisfied with the prevailing level of QoL. This in turn is associated with the transitional nature of this neighborhood. The residents were strongly dissatisfied with regard to the environmental qualification as opposed to accessibility status. Furthermore, this study identified five objective factors respectively regarding QoL. There exists low correlation between subjective and objective dimensions. That demands simultaneous consideration of both objective and subjective dimensions. It is argued that individual treatments of each could not accurately represent the QoL of residents.     

Health Disorder of Climate Migrants in Khulna City: An Urban Slum Perspective

As the most vulnerable climatic region in the country, Khulna City is increasingly experiencing climate‐change‐induced urban problems. For instance, occupancy by climate migrants (delete the term “illegal migrant”), drainage congestion, water logging and reduced fresh water availability are all increasing problems. In the last decade, the population in the city increased by more than 20 per cent due to migration from nearby climate vulnerable districts. This study explores the health disorders of climate migrants occupying the urban slums and squats of the Khulna City area. This study found that these climate migrants settled in the urban slums and squats and, as such, they do not have access to urban amenities such as clean drinking water, hygiene services, and health facilities. This study noted that these displaced people are at increased risk of health issues from unhygienic and overcrowded living conditions and from water and sanitation problems. They often suffer from different waterborne diseases, under‐nutrition and micronutrient deficiencies. This study suggests that there is a need for better planning, preparation and training in Bangladesh to which migrants move, including better training in health and related services on how to recognize and respond to health problems that may be slow to manifest. Education and training also need to be provided for the migrants themselves, to help them adapt culturally and to enhance their skills and potential for employment.     

On bias reduction estimators of skew-normal and skew-t distributions

A particular concerns of researchers in statistical inference is bias in parameters estimation. Maximum likelihood estimators are often biased and for small sample size, the first order bias of them can be large and so it may influence the efficiency of the estimator. There are different methods for reduction of this bias. In this paper, we proposed a modified maximum likelihood estimator for the shape parameter of two popular skew distributions, namely skew-normal and skew-t, by offering a new method. We show that this estimator has lower asymptotic bias than the maximum likelihood estimator and is more efficient than those based on the existing methods.     

A flexible generalization of the skew normal distribution based on a weighted normal distribution

The skew normal distribution of Azzalini (Scand J Stat 12:171–178, 1985) has been found suitable for unimodal density but with some skewness present. Through this article, we introduce a flexible extension of the Azzalini (Scand J Stat 12:171–178, 1985) skew normal distribution based on a symmetric component normal distribution (Gui et al. in J Stat Theory Appl 12(1):55–66, 2013). The proposed model can efficiently capture the bimodality, skewness and kurtosis criteria and heavy-tail property. The paper presents various basic properties of this family of distributions and provides two stochastic representations which are useful for obtaining theoretical properties and to simulate from the distribution. Further, maximum likelihood estimation of the parameters is studied numerically by simulation and the distribution is investigated by carrying out comparative fitting of three real datasets.     

New Ridge Regression Estimator in Semiparametric Regression Models

In the context of ridge regression, the estimation of shrinkage parameter plays an important role in analyzing data. Many efforts have been put to develop the computation of risk function in different full-parametric ridge regression approaches using eigenvalues and then bringing an efficient estimator of shrinkage parameter based on them. In this respect, the estimation of shrinkage parameter is neglected for semiparametric regression model. Not restricted, but the main focus of this approach is to develop necessary tools for computing the risk function of regression coefficient based on the eigenvalues of design matrix in semiparametric regression. For this purpose the differencing methodology is applied. We also propose a new estimator for shrinkage parameter which is of harmonic type mean of ridge estimators. It is shown that this estimator performs better than all the existing ones for the regression coefficient. For our proposal, a Monte Carlo simulation study and a real dataset analysis related to housing attributes are conducted to illustrate the efficiency of shrinkage estimators based on the minimum risk and mean squared error criteria.